# -*- coding: utf-8 -*-
from datetime import timedelta

from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from jms_hi.dim.dim_network_whole_massage import jms_dim__dim_network_whole_massage
from jms_hi.dwd.oms.dwd_yl_oms_oms_order_hf import jms_dwd__dwd_yl_oms_oms_order_hf
from jms_hi.dwd.oms.dwd_yl_oms_order_third_ext_base_hi import jms_dwd__dwd_yl_oms_order_third_ext_base_hi

from airflow.exceptions import AirflowSkipException
import pendulum
cst = pendulum.timezone('Asia/Shanghai')
class HiSparksqlOperator(SparkSqlOperator):
    def pre_execute(self, context):
        day = cst.convert(context['ti'].execution_date) + timedelta(days=1)
        days_of_hours = ['05', '06', '07', '08', '09','10','11','12','13','14','15','16','17','18','19','20','21','22','23']
        if day.strftime('%H') not in days_of_hours:
            print(f'{day.strftime("%H")} not in {days_of_hours}, should skip')
            raise AirflowSkipException()
        else:
            print(f'{day.strftime("%H")} in {days_of_hours}, run now')
            super().pre_execute(context)

jms_dm__dm_mng_station_arrival_prediction_order_detail_dt = HiSparksqlOperator(
    task_id='jms_dm__dm_mng_station_arrival_prediction_order_detail_dt',
    task_concurrency=1,
    pool_slots=3,
    master='yarn',
    execution_timeout=timedelta(hours=1),
    email=['shenjiaming@jtexpress.com', 'yl_bigdata@yl-scm.com'],
    name='jms_dm__dm_mng_station_arrival_prediction_order_detail_dt_{{ execution_date | cst_hour }}',
    sql='jms_hi/dm/mng_report/dm_mng_station_arrival_prediction_order_detail_dt/execute.sql',
    driver_memory='4G',
    driver_cores=4,
    executor_cores=4,
    executor_memory='8G',
    num_executors=20,
    conf={
        'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
        'spark.shuffle.service.enabled': 'true',  # 动态资源 Shuffle 服务开启
        'spark.dynamicAllocation.maxExecutors': 30,
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 120,  # 动态资源自动释放闲置 Executor 的超时时间(s)
        'spark.executor.memoryOverhead': '1G',
        'spark.hadoop.hive.exec.dynamic.partition.mode': 'nonstrict',  # 动态分区
        'spark.hadoop.hive.exec.dynamic.partition': 'true',
        'spark.default.parallelism': 120,
        'spark.sql.shuffle.partitions': 360
    },
    hiveconf={'hive.exec.dynamic.partition': 'true',
              'hive.exec.dynamic.partition.mode': 'nonstrict',
              'hive.exec.max.dynamic.partitions.pernode': 200,
              'hive.exec.max.dynamic.partitions': 200
              },
    yarn_queue='pro',
)

jms_dm__dm_mng_station_arrival_prediction_order_detail_dt << [
    jms_dim__dim_network_whole_massage
    , jms_dwd__dwd_yl_oms_oms_order_hf
    , jms_dwd__dwd_yl_oms_order_third_ext_base_hi
]
